{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import torch\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from sklearn.feature_extraction import image\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "dropout = np.load('test_preds/drop_v2/preds.npz')\n",
    "swag = np.load('test_preds/swag_scale_05_v2/preds.npz')\n",
    "swag_diag = np.load('test_preds/swag_diag_v2/preds.npz')\n",
    "swa = np.load('test_preds/sgd/swa_preds.npz')\n",
    "sgd = np.load('test_preds/sgd/sgd_preds.npz')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def softmax(x, axis=1):\n",
    "    return np.exp(x) / np.sum(np.exp(x),axis=axis, keepdims=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def compute_local_accuracy(predictions, labels, patch_size = 4, background_label = 11):\n",
    "    \n",
    "    acc_list = []\n",
    "    for i, (pred, label)in enumerate(zip(predictions, labels)):\n",
    "        if i % 10 is 0:\n",
    "            print(i)\n",
    "        pred_patches = image.extract_patches_2d(pred, (patch_size, patch_size))\n",
    "        label_patches = image.extract_patches_2d(label, (patch_size, patch_size))\n",
    "        \n",
    "        background_patches = label_patches == background_label\n",
    "        #mean_accuracy = (pred_patches == label_patches & ~background_patches).mean(axis=(1,2))\n",
    "        mean_accuracy = np.sum((pred_patches == label_patches) & ~ background_patches, axis=(1,2)) / np.sum(~background_patches, axis=(1,2))        \n",
    "        acc_list.append(mean_accuracy)\n",
    "    return acc_list\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def compute_local_confidence(max_predictions, patch_size = 4):\n",
    "    conf_list = []\n",
    "    for pred in max_predictions:\n",
    "        pred_patches = image.extract_patches_2d(pred, (patch_size, patch_size))\n",
    "        mean_conf = pred_patches.mean(axis=(1,2))\n",
    "        conf_list.append(mean_conf)\n",
    "    return conf_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/wesley/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:12: RuntimeWarning: divide by zero encountered in true_divide\n",
      "  if sys.path[0] == '':\n",
      "/home/wesley/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:12: RuntimeWarning: invalid value encountered in true_divide\n",
      "  if sys.path[0] == '':\n"
     ]
    },
    {
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    }
   ],
   "source": [
    "drop_acc = np.array(compute_local_accuracy(np.argmax(dropout['predictions'],1), dropout['targets']))\n",
    "drop_conf = np.array(compute_local_confidence(np.max(dropout['predictions'],1)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n"
     ]
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    {
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     "text": [
      "/home/wesley/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:12: RuntimeWarning: divide by zero encountered in true_divide\n",
      "  if sys.path[0] == '':\n",
      "/home/wesley/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:12: RuntimeWarning: invalid value encountered in true_divide\n",
      "  if sys.path[0] == '':\n"
     ]
    },
    {
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    }
   ],
   "source": [
    "swag_acc = np.array(compute_local_accuracy(np.argmax(swag['predictions'],1), swag['targets']))\n",
    "swag_conf = np.array(compute_local_confidence(np.max(swag['predictions'],1)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n"
     ]
    },
    {
     "name": "stderr",
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     "text": [
      "/home/wesley/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:12: RuntimeWarning: divide by zero encountered in true_divide\n",
      "  if sys.path[0] == '':\n",
      "/home/wesley/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:12: RuntimeWarning: invalid value encountered in true_divide\n",
      "  if sys.path[0] == '':\n"
     ]
    },
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   ],
   "source": [
    "swag_diag_acc = np.array(compute_local_accuracy(np.argmax(swag_diag['predictions'],1), swag_diag['targets']))\n",
    "swag_diag_conf = np.array(compute_local_confidence(np.max(swag_diag['predictions'],1)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     "text": [
      "/home/wesley/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:12: RuntimeWarning: divide by zero encountered in true_divide\n",
      "  if sys.path[0] == '':\n",
      "/home/wesley/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:12: RuntimeWarning: invalid value encountered in true_divide\n",
      "  if sys.path[0] == '':\n"
     ]
    },
    {
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    }
   ],
   "source": [
    "swa_acc = np.array(compute_local_accuracy(np.argmax(swa['preds'],1), swa['targets']))\n",
    "swa_conf = np.array(compute_local_confidence(np.max(softmax(swa['preds'],1),1)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "/home/wesley/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:12: RuntimeWarning: divide by zero encountered in true_divide\n",
      "  if sys.path[0] == '':\n",
      "/home/wesley/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:12: RuntimeWarning: invalid value encountered in true_divide\n",
      "  if sys.path[0] == '':\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
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   ],
   "source": [
    "sgd_acc = np.array(compute_local_accuracy(np.argmax(sgd['preds'],1), sgd['targets']))\n",
    "sgd_conf = np.array(compute_local_confidence(np.max(softmax(sgd['preds'],1),1)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "unc_thresholds = np.arange(0., 1., 0.05)\n",
    "\n",
    "def conditional_acc_unc(acc, conf, thresholds = unc_thresholds, acc_threshold = 0.5):\n",
    "    mean_acc = np.zeros_like(thresholds)\n",
    "    mean_unc = np.zeros_like(thresholds)\n",
    "    pa_vpu = np.zeros_like(thresholds)\n",
    "    for i, u in enumerate(thresholds):\n",
    "        ac = ((conf > u) & (acc > acc_threshold)).sum()\n",
    "        ic = ((conf > u) & (acc < acc_threshold)).sum()\n",
    "        \n",
    "        iu = ((conf < u) & (acc < acc_threshold)).sum()\n",
    "        au = ((conf < u) & (acc > acc_threshold)).sum()\n",
    "        mean_acc[i] = ac / (ac + ic)\n",
    "        mean_unc[i] = iu / (ic + iu)\n",
    "        pa_vpu[i] = (ac + iu) / (ac + au + ic + iu)\n",
    "        \n",
    "        \n",
    "    return mean_acc, mean_unc, pa_vpu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/wesley/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:1: RuntimeWarning: invalid value encountered in greater\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "1123027"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "((drop_acc > 0.2) & (drop_conf < 0.5)).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/wesley/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:8: RuntimeWarning: invalid value encountered in greater\n",
      "  \n",
      "/home/wesley/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:9: RuntimeWarning: invalid value encountered in less\n",
      "  if __name__ == '__main__':\n",
      "/home/wesley/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:11: RuntimeWarning: invalid value encountered in less\n",
      "  # This is added back by InteractiveShellApp.init_path()\n",
      "/home/wesley/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:12: RuntimeWarning: invalid value encountered in greater\n",
      "  if sys.path[0] == '':\n"
     ]
    }
   ],
   "source": [
    "drop_mean_acc, drop_mean_unc, drop_pa = conditional_acc_unc(drop_acc, drop_conf)\n",
    "swa_mean_acc, swa_mean_unc, swa_pa = conditional_acc_unc(swa_acc, swa_conf)\n",
    "sgd_mean_acc, sgd_mean_unc, sgd_pa = conditional_acc_unc(sgd_acc, sgd_conf)\n",
    "swag_diag_mean_acc, swag_diag_mean_unc, swag_diag_pa = conditional_acc_unc(swag_diag_acc, swag_diag_conf)\n",
    "swag_mean_acc, swag_mean_unc, swag_pa = conditional_acc_unc(swag_acc, swag_conf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(1-unc_thresholds, drop_mean_acc, label = 'Dropout')\n",
    "plt.plot(1-unc_thresholds, swa_mean_acc, label = 'SWA')\n",
    "plt.plot(1-unc_thresholds, swag_mean_acc, label = 'SWAG')\n",
    "plt.plot(1-unc_thresholds, swag_diag_mean_acc, label = 'SWAG-Diag')\n",
    "plt.plot(1-unc_thresholds, sgd_mean_acc, label = 'SGD')\n",
    "plt.xlabel('Uncertainty (1 - Max Prob)')\n",
    "plt.ylabel('P(Accurate | Confident)')\n",
    "plt.grid()\n",
    "plt.legend()\n",
    "plt.savefig('/home/wesley/Documents/Papers/udl_paper_source/icml/plots/pics/segmentation_acc_conf.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Uy9icR0+VL5ibBT2r0nnWgdQnhyr45M1e69QVxVD6/rLX502Wq5oi7Xbp0qVZvnz5sz4mT57MnTt3qFjRoO0CWVbOeWIAsLCA5tPAzg2WdoH4e689VQhB7fYlcPd2ZPOcU0Rfe2CyYZUt4MTCXlVJTE6hzbT9nL31+nkQRVHSz1Rpt+vWrUtCQgJTp0591vajR9n/yT9nBQbQvVJqPQdir8PKIEhjdazGyoJGfcpirdWwbmoYCQ9Nt/egVD5HFvepioWAdsH7OXldpe1WlIxiqrTbQghWrlzJjh078Pb2pnLlynTp0oUff/zR7PeYkQxKiSGEsAD8gfxAPHBSSnnLxGN7rTdNuw3Avimw4XOo/y3U+DjNU29evM/fvxzBs5gzjQf4Y2HC2s6X7zykw/T9PHySzJ/dK+Pv9WKluey48zUjqfvPfvev0m5nnCyRdlsIUUQIEQycB8YC7YEgYJMQYr8Qoltq0Mh+qvaDUk1g8yjdvEMaPHycqN2+BBGn7rF72XmTZkot7GrH4j7VcMxlSacZBwi5krGZXxVFUfTR90v9O+AvoIiU8j0pZScpZSsppR/wIbpU2Z1NPUiTEAKaTgbngrC0GzxMe7ezb438+Nfz4vi2SEI3mbbGgpeLLUv6VMPVwYbOMw+y/2K0SftTFEV5XpqBQUrZXkq581VpKqSUUVLK36SUc003PBPTOkGbufAoGlb0gpS0S33WaFGUohXc2LviPGcP3TTp0PI55WJxb93ehq6zD7LrnNlTSCmKkkMZ9BpICGErhPhKCDE99XMxIURj0w7NTPL5Q6Mf4cJW2PlzmqcKC8G7XUuRv5gzW+acyvACPy9zc9SyqHdVvF3t6TH3MFtOZdq0jqIoOYih8wOzgcdAtdTPkeheM70dKnQFv7aw/Qe4uD3NUy2tNLzfryzO7ras/+M4dyJNt4wVII+9DQt7VaGkhwN9/woh5JZp0nQoiqI8ZWhgKCKl/AlIBJBSxgMZnyciswgBH/wCrsVheU+IvZHm6Ta2VjQe4I+V1pI1E0OJu2vaXEfOttb81bMKZT2dmBL6mI0nTfsaS1GUnM3QwPBECJELXY1mhBBF0D1BvD1s7KHNn/DkISzrDslp/2Xu4KKlyUB/Eh8ns3riMZPucQBw1Foxt3tlCjla0H/BEfVaSVHSKSuk3e7atSve3t74+/tTvHhxPvroI65du/bs+++//z4xMTEZdctGMzQwjAL+BbyEEPOBLcCb7W3PitxKQuPf4Ope2Pqt3tPzeNrTqJ8f928/Yt3UMJIS0568flMOWiv+V1FLqXyO9PvrCNvP/KfQnaIor5CV0m6PGzeOY8eOcebMGcqVK0edOnV48kRXm2XdunU4Ozu/9lpzMSgwpNZJaAF0RVdQp6KUcpsJx5V5/Nvq5hz2/AZn/tV7eoESuanX1Zcb5++zeXY4MsW0dYbsrATzulehmLs9veeFqNVKimKArJh2WwjB4MGD8fDwYP369QAULlyYO3d0S+ebNWtGhQoVKF26NMHBwc+umzlzJsWLFycwMJBevXoxYMCAN/3x/IdBSfSEEFuklO8Ca1/xtbdPwx/hWgj83Qf67ITchdI8vVhFdx7GPGbPsvPsXnqOmm2KZXjd6Oc52VrxV48qdJhxgJ5zDzO7ayWqF3U1WX+KklFufv89j08Zn3Y7KTmZuy+l3bYpVRKPESPSvC4rp90uX748p0+fpmnTpi98fdasWbi4uBAfH0+lSpVo2bIl0dHRfPvttxw5cgQHBwfq1q2Lv7//G/X/Kvp2PmuFEC6AqxAitxDCJfUojC49xtvJSgut54JMgaVdIUl/Cc6AegXxf9eLMDNsgAPIbWfN/J5V8Ha1o/vcQ2oTnKKkISun3X5dJoUJEybg7+9P1apViYiI4Ny5c4SEhFC7dm1cXFywsrKidevW6fxJGEbfE0Mf4BN0QSCE/1+JFAtMNsmIsoo8RXQ7o5d0ho1fwvs/6b2kRsuiPIx5zN4V57HLbU3xSh4mHaKLnW61Uvvg/XSfc4g53SpT2dvFpH0qypvQ95e9Ptkt7Xa3bt04evQo+fPnZ926da8c19GjR3n33Rdfvmzfvp3Nmzezb98+bG1tCQwMJCEhwaTpeJ6nb+fz71JKb2CIlNJHSumdevhLKSeZZYSZyfdDqBoEB6fBSf3Fvc29AQ7A1d6GBb2qks9JS7fZB1VuJUV5hcxKuz179mxCQ0NfGRSklEyYMIEbN27QsGHDF753//59cufOja2tLadPn2b/fl0+twoVKrBjxw7u3btHUlLSC0EpIxk6+TxRCFFGCNFGCPHR08MkI8pq6o2GApXgn4Fw57ze0829AQ4gr4MNC3tVxd1RS5dZhzh69fV1JhQlJ8pKabeHDh36bLnqoUOH2LZtG9bW1i+c07BhQ5KSkvDz8+Orr76iatWqAOTPn58RI0ZQpUoV6tWrh6+vL05OThn5o9KRUuo9gJHANuAWul3QN4FlhlxriqNChQrSGE+uX5fJ8fHpv/DeVSnHFpJySnUpnzwy6JLY6Hg5e9huOfuzXTI22og+X2Pbtm2v/d6NmHhZ66etsszX/8rQq/cyrM+sJK37zwmy4/2Hh4dnWFuxsbEZ1lZ2FBsbK+Pi4qSUUiYmJsrGjRvLFStW/Oe8V/3MgcPSwN+xhu5jaAW8C9yUUnZDV5vBJsOjlAklx8RwqVlzbn3/Q/ovdvaCFtPh1glYPSjN4j5PmXsDHICHk5aFvaribGdF55kHOHFNFftRlLfNqFGjCAgIoEyZMnh7e7+wSS+jGBoY4qWUKUCSEMIRiAJ8Mnw0JqRxdsa5dStiliwh9jWTQGkqVh/qfAFhi/Um23vK3BvgAPI752Jhr6o4aK3oOOOAqgSnKG+Zn3/+mdDQUE6fPs2ECRNMsjTe0MBwWAjhDExHtzrpCHAww0djYnkHDSKXvz83vvqaJ1evpr+BWkN1yfa2fQcnDJv0MfcGOIACuW1Z2KsqdtYaOs04wOmbsSbvU1GUt4fewCB04egHKWWMlPIPoD7QJfWVUraSpIH8438GjYZrgz8l5Yn+/QkvEAI+nAgFq8Hf/SDCsNhYrKI7NVoV5cKR2+xees4sS84K5rFlQa+q2Fhq6Dj9AGdvxZm8T0VR3g56A0PqpMXK5z5fllKGmXRUJnD/8X26rO/C8ge7yP/9GBJOnuT2+PHpb8jSBtrOB8d8sLA93Lti0GUB9QriX9d8G+BAVyZ0Qa8qaCwEHabv53yUCg6Kouhn6Kuk/UIIw7fyZUEO1g442zgz7tA4rpUvQO5Onbg790/itm5Nf2N2eaDDUkhJhAVtIcGw9/g1WpmvAtxTPnntWdCrKiBoP/0AF2+bfvmsoijZm6GBoQ6wTwhxQQgRJoQ4LoTIVk8NFsKCMTXHkNsmN0N3DMVhcH+0vr5c/3wEidevp7/BvMV1abqjz+nSZuhJ0w2ZswEOoKibPQt7VSElRdJpxgFu3I83S7+KkpW8nHb7wIEDJCUlMWLECIoVK0ZAQAABAQGMGTPm2TUajYaAgABKly6Nv78/v/zyCykpKZl4F+ZhaGBoBBQB6gJNgMap/8xWcmtzM7bWWK7GXWXMkZ/w/PUXSEri2v+GIBONWE7qE6gr8HNhK6z/zKBlrJZWGhr1Ne8GOIBi7g7M7V6Z2IQkOs88yL2H6ZxfUZRs7FVpt728vPjyyy+5fv06x48fJzQ0lF27dpH43O+CXLlyERoaysmTJ9m0aRPr1q1j9OjRmXgn5mFoYJCvObKdSh6V6OvXl9UXV7M+MRSP0aOJP3qU2xONzPBRoQvUGASHZ8KBPwy6RGtn3gpwT5XxdGL6RxW5Gv2I7nMP8eiJKhOq5AyvSrvt7OzM9OnTmThx4rNkeQ4ODowaNeqVbbi5uREcHMykSZPMlrMosxiUdhtdum2JLomeFvAGzgClTTQuk+rt15uDNw8y5sAY/Bovxrl1K6KDg7GtXBn7mjX0N/Cyd0dB9AX493PI7Q0lGuq95OkGuBXjQlg98RgthpRHa2eV/r7TqVqRPExoH0DQ/CP0++sIM7pUxEpj6N8HivJmdi05y50I45+Sk5OT0byUdtvVy5532hRP87pXpd3OnTs3BQsWTFdSPh8fH1JSUoiKisLd3d2oe8gODM2VVFZK6Zf6z2JAZWC3aYdmOhoLDWPfGYtWo2XIjiE4D/sfNsWKcn3YMBKjjKiKZmEBLYIhn7+uLOjN4wZd9mwDXNQj1v9x3Cwb4AAalsnHmOZl2XH2NkOXHiPFDHsrFCUzvSrt9vbt2184Z/bs2QQEBODl5UVExOtXDr7tTwuAYbmSXnUAR4y99k0PY3MlvWxHxA5ZZk4Z+e2+b2XCuXPylH+AvNylq0xJSjKuwfvXpRxfSnfcv27wZWcO3pCT+myR66cdlynJKWmem5G5ciZtPScLDVsjR606IVNS0u43q8iOuYIyUna8/6yYK2np0qWyXr160sXF5T9tli5dWl66dElKKaWdnd0L37tw4YJ0cXHJtP9fDL1/s+RKEkJ8+twxRAixANBbU1II0VAIcUYIcV4IMfw157QRQoQLIU6mtms2tQrUootvFxafWcxOq0t4fPUlj/bv5860acY16JgPOiyG+BhY2A6ePDTosuKVPKjeoigXjkSxZ5n+DK4ZJSiwCN1qFGb2nstM2X7BbP0qirm9Ku12iRIl6NGjBwMGDHhWqjM5OflZ/eWX3b59m759+zJgwACTVmjMCgydY3j+JVwSujmHNHNCCCE06Ir51AcigUNCiFVSyvDnzikGfA7UkFLeE0K4pWfwGWFQ+UGE3Aph5J6RLGmyBMf9TbgzaTJ2lSphm44qTM94lIVWs2BRe1jRG9rM071q0iOgvhcP7iVwbGsE9i42BNQraMTdpI8Qgq8+8OXuwyeM23CGPHbWtKts+n4VxdwePHjAwIEDiYmJwdLSkqJFixIcHIyTkxNfffUVZcqUwcHBgVy5ctGlSxfy59cVqIyPjycgIIDExEQsLS3p3Lkzn376aSbfjekZFBiklMasz6oMnJdSXgQQQiwCmgLhz53TC5gspbyX2o8RL/jfjJXGip9q/0Sb1W0YtmsYs76eTEJYGNf+NwTvlX9j6WJERbQSDeG97+Hf4bBlFNT/Ru8lQghqtC7Gw/u62tF2TjYUq2T6yS0LC8G4Vv7EPEpkxN/Hcba1pmEZ01aeUxRzq1ChAnv37n3l98aOHcvYsWNf+b3kZPPM+2U1hr5K2pSaRO/p59xCiA16LvMEnp/BiUz92vOKA8WFEHuEEPuFEPqX85iAl4MXI6uPJOx2GFPOzsbz119IvneP68OHI43dzFKlL1TqCXt+h5C5Bl1iYSGo182XfEWd2Dw3nGtnzFNwx9rSgqmdyuNXwJmPFx1l3wVVP1pRcjJDXyXllVLGPP1g4GufV72Ee3k63xIoBgQCBYBdQogyz/f1rDEhegO9Adzd3f+zouBNadFSw74Gs07MQuumpXzLFshFizn05Vc8alDfqDZFrvcpmzsE5zWDCbt6n5jcfgZd51hWcjdKsmrSUbzfFWid//9H+eDBgwy/96d6FpN8f1fSbdZ+Pq+ipZCjRv9FZmbK+88OsuP9Ozk5EReXMXm6kpOTM6yt7MjQ+39at9pohsxQo0u1XfC5z4XQsyoJqAZseO7z58DnL53zB9D1uc9bgEr6xpNRq5JeFp8YL5utbCZrLaolbz24JSMGDJDhpcvIR6Ghb9BojJSTqkj5g5eUUWcMviw2Ol7O/myXnD1s9wsV4Ey9KuXavUey2vebZYVvN8pLtx+YtC9jZMdVORkpO95/eHh4hq3iURXc9N9/SkqK2Sq4fQHsFkLME0LMA3am/qJPyyGgmBDCWwhhDbQDVr10zkp0eZgQQriie7V00cAxZTitpZafa//Mo8RHjNg9ArdvRmPl5sa1wZ+SfN/IgjdaJ91KJY01LGgNDw17TePgoqXxQH+eJCSxZtIxHj8yfQU40BX6+bNHFZJTJB/NOkhUrHl2ZStvL61WS3R0dM5Y/5/JpJRER0c/28ltLEMnn/8VQpQHdGk6YbCU8o6ea5KEEAOADYAGmCWlPCmE+AZd5FqV+r0GQohwIBkYKqXM1BfcRZyL8HmVzxm5dyRzIpabgMJIAAAgAElEQVTR+ZfxXO7UmRtffoXnhN+NW6aWuxC0WwhzPtCtVvroH7DKpfcy1wIONOpbljUTj7Fu6nE+/DjAiDtKv6Ju9szuVpkO0/fTZfYhFvWuilMu0+/KVt5OBQoUIDIyktu39a5w1yshIeGNf+llZ4bcv1arpUCBAm/WkSGPFUBzwOm5z85AM0MfSzL6MNWrpKdSUlLk0B1Dpd9cPxlyM0TemTFThpcoKaPnz3+zhk/8LeVIJykXd5YyOdngy07v122A+zf4uNy6deubjSEddpyJkkVHrJWt/9gr458Yuekvg2XHVykZSd3/tsweQqZ6k/vHBK+SRkopn71LkbrJ4ZFvFpKyLiEEX1f9Gk97Tz7b+RkW7ZthV+sdon4YS0J4uP4GXqd0M3hvDIT/Axu/NPiyElU8qNa8COdDorgVar7H8VrF8/Jza38OXb7LwIVHSUp++9MNK4pieHbVV51n6IqmbMne2p5xtccRnRDN1/tHku+HH9C4uBAR1J/Em29QZKdqkG4p6/7JsH+qwZeVa1CQsrU9iT4Dx7dHGt9/OjUN8GRUk9JsCr/FiL+Pq/fEipIDGBoYDgshfhFCFBFC+AghfkW3UumtVjpPaT6t8CnbI7az+NZ6vP6YSkpsLBF9+pL8wMgMkULoNr+VbKzLxhr+8nz86y4T1GxbHIf8sGvxWS6HpTnFk6G6VC/Mx+8WY8nhSH7eeMZs/SqKkjkMDQwDgSfAYmApkAD0N9WgspJOpToRWCCQ8SHjueCWgueECTy+cIFrH3+MfE1OFb0sNNByBhSoCCt6wdUDhl1mIShQXeDq5cCGGSeIuhJrXP9GGFyvGO0rezF52wUWHbxqtn4VRTE/Q9NuP5RSDpdSVpRSVpBSfi6lNCxDXDYnhODbGt+SR5uHz3Z8hqgSQL5vvuHh3n3c+Opr41+tWOWC9ovAMb8u4V60YUnsLCwFH/T3Q2tvxdrJYWYr8iOE4NumZahdPC9frDzBzrNvvsJEUZSsydCUGHmFEOOEEOuEEFufHqYeXFbhrHXmx1o/Evkgks93fY5Dsw9xHTiA+//8w+0JE4xv2M4VOi7TvV76qyU8MOyXrZ2TDY0H+JOUmGLWPQ6WGgsmdShHMTd7guYf4dQN8z2xKIpiPoa+SpoPnEZXuW00cBndBrYco4J7BT6r9BnbIrYx9uBY8vTrh1OrlkRP/YN7S5YY33CeItB+McTdSE3V/ciwy/Lb06hPGWJuPmL9tBMkJ5lnxZCD1orZ3SphZ6Oh+5xD3FIb4BTlrWNoYMgjpZwJJEopd0gpu6Pb7JajdCzVkS6+XVh0ZhFzw+eSb+RI7GrW5Obob3iwc6fxDXtV0s05XAuB5T0hxbCMjgVKulCnc0munbnH9vmnzbZiKJ9TLmZ1rURsfCLd5xzi4WNVO1pR3iaGBoan7ypuCCE+EEKUQ5f0Lsf5tOKnvFf4PX4J+YX1EZvw/O03bEoUJ/KTwcSfOGl8w6WaQKMf4cxaXbpuA3/Jl6yWj0ofFOb0vpscXnfZ+P7TqXR+JyZ1LM/pm3Fqj4OivGUMDQzfCSGcgP8BQ4AZwGCTjSoLsxAWjKk5hgruFfhyz5cceRCO1x9/oHF2IqJvX55EXjO+8Sp9oNoAOBgM+yYZfFmlxt6UqOLBwdWXOHPgDfZYpFOdEm5807Q0W09HMWr1SbXHQVHeEoauSlojpbwvpTwhpayTujLJsAX4byEbjQ2/1/kdLwcvBm0dxBWrWAoGByOfPCGid2+SY/6TNdxw9b8F32a6ndEnVhh0iRCCOp1L4lnCma1/njJbHQeAjlUK0aeWD3/tv8qMXZfM1q+iKKaTnlVJI4QQwUKIWU8PUw8uK3OycWJqvanYWNrQb0s/YvI54DV5EokREUQMGEDK48fGNWxhAc2ngVdV+LsPXHl11amXaSwtaNi7LE55c7F+2nHu3jDfauJhDUvyflkPvl9/ivXHb5itX0VRTMPQV0n/AE7AZnT1np8eOVp++/xMeXcKsY9jCdoSRIp/KfKN/YH4wyFvVv3NSgvtF4JzIVjYHm6fNegyrZ0VjQf4Y2FpwZpJx3gUa+QGvHSysBD80iaAcl7OfLI4lCNXzffEoihKxjM0MNhKKYdJKZdIKZc/PUw6smyiVJ5S/Br4KxdjLjJ4+2BsGzbAbegQ4tb/S9S4n41v2NYFOi4FjRXMbwlxtwy6zNE1F437+xEf94S1k4+R+MQ8NWu1Vhqmf1QRd0ctveYe5mq0YctuFUXJegwNDGuEEO+bdCTZWHXP6oysPpL9N/Yzat8ocnfrRu4OHbg7ezZ35/1lfMMu3roiPw/vwII28MSw10NuhRxp0KM0UVfj2DTzJCkp5pkUzmNvw5xulUiWkq5zDhLzyDxPLIqiZCxDA8MgdMEhXggRK4SIE0Koba/PaVa0GUEBQay6sIrJxybj/sUI7N99l1vff0/spk3GN+xZAVrNgpthsLQbwsA9Dt7+eXmnTTEuHbvD3mXnje8/nXzy2hPcuSKRd+PpPS+Ex0nmeWJRFCXjGLoqyUFKaSGlzCWldEz97GjqwWU3ff360qJYC4LDgll2YQWeP49D61eW60OG8ujoUeMbLtEI3h8H5zZQ7Nw0g/c4+NXxwr+uF8e2RnBsa4Tx/adTZW8XxrX24+CluwxbFqaWsSpKNpNmTYXUcp6vJaU8krHDyd6EEHxZ9UuiHkXx3f7vcLd1p/rUqVxu357IfkEUXrQQ68KFjWu8Uk+IiSD/nt9g589Qe6hBl1VvVZTY6Hh2Lz2Hg4sWn4C8xvWfTk0DPIm8F8+4DWco6GLLpw1KmKVfRVHenL4nhvFpHG8ws/r2srKwYnzt8ZTIXYIhO4ZwJuUGBYODQQiu9u5DUvQblLR+dyQ33QNh23dwdL5Bl1hYCOr3KI1bQQc2zTzJrcvmewMYFFiEthW9mLD1PEsOm++JRVGUN5NmYEjdzPa6o665Bpnd2FrZMqXeFFy0LgRtCeKWiwVeU6eQFBVFRK/eJMfFGdewhQVnSgwAn0BYNRDObTboMitrDR/09yeXozXrppg3Vfd3zctQs6grI1YcZ8958xUXUhTFeIZOPivp5JrLlSn1ppCUkkS/zf1IKFmIAr//RsLZs0T07UdKfLxR7UoLK2gzD9x9YclHcN2wuQtbR2sa9/cn6Ukyaycf40mCeRLfWWksmNKpPEXy2tN3XghnbxkZFBVFMRsVGEzIx8mHiXUncuPBDQZuHYhljSp4jvuJ+KNHiRz4MSnGVoDTOurqONjmgfmt4a5hqShc8tvRsHdZ7t54xMYZJ0kxU+I7R60Vs7pVQmutocfcQ9x7qJaxKkpWpgKDiZV3L8/YWmMJux3G8F3DsXuvAfm+Gc3D3bu5PmQoMsnIv9wdPKDTckhJ0hX5eWjYaxovXxdqtSvOlRPR7DHjMlZP51wEd67ArfuPVTZWRcniVGAwg/qF6vNZpc/YcnULPxz8AaeWLXEbPoy4jRt15UGNTZ2Rt7iuPGjsNVjQ1uAiP2VqeeL/rhdh2yI5vj3SuL6NUK5gbr5rXobd5+/w47+nzdavoijpo2+56iUgrUXoIvX7v0kp36DG5duvk28nouKjmH1iNrZWtgzuMpiUBw+5M2kSFvb2uI/4HCFE+hsuWFVX5GdxZ1jWHdr+BZo0/7MCUL1lUe7fjmfXknM45s1FodJ5jLir9GtT0YuT1+4zfdclSud3olk5T7P0qyiK4dL8DSKl9DbXQHKCweUH8yjxEbNPzMbO0o7e/YNIiYvj7ty5WNjb4TZokHENl2qi2wC3bgis+x80/k1XRzoNFhaC+t19+Xv8ETZMP0HLoRXI42lvXP/p9GVjX07djGPY8jCKutlTxtPJLP0qimIY9SrJjIQQjKgygg+LfMik0EnMC5+H2/BhOLduRfTUP4ieOdP4xiv3gpqfQsgc3QY4A1hrLfkgyA8rGw1rJ4eZLRurlcaCKR3Lk8fOmt5/HubOAyNTlCuKYhIqMJiZhbBgdPXR1C9Un3GHx7H83HI8Ro3C8f1GRI37mXuLFhvf+Ltfg1+71A1whiXvs8+t5YMgP+IfPGHd1DCSzJSN1dXehuCPKhL98AlB84+QqCajFSXLUIEhE1haWPLjOz9S07Mm3+z7hnVX/iX/2LHY1a7FzdGjub/GyFIXQsCHE8GnDqz6GM4ZlrzPrZAj9buV5tblWLb8eQpppmysZTyd+LGlLqfSd2vCzdKnoij6qcCQSaw0Vvwa+CsVPSryxe4v2HpzFwV+/x3bihW5PmwYcVu3GtewpTW0nQfupWFJF7hmWDorn3J5qdasCOcPR3FwjflKdDYr50mvd7yZu+8KSw6ptBmKkhUYWtqzuBBiuhBioxBi69PD1IN722kttUysO5HSeUozdMdQ9kcfocDUqWh9fbn2yWAe7ttnXMM2DroiP7Z5dHUcDNwAV65BQUrVyMfhdZc5s998JTqHNSxJzaKufLnyhKr+pihZgKFPDEuBI8CXwNDnDuUN2VnZMaXeFHycfBi0bRChD0/jFTwN60KFiOg/gPjQUOMaNmIDnBCC2u1L4FnCma1/neb6uRjj+k4nS40FE9uXw93Jhr7zQoiKNU8uJ0VRXs3QwJAkpZwqpTwopQx5eph0ZDmIk40T0+pPw8POg/5b+nM6+RpeM2dg6erK1d59SDht5GawvMWh/eLUDXCGVYDTWFrQsHdZHPPkYv0fx4mJMk+Jztx21kz/qCJxCUn0/UsV+FGUzGRoYFgthAgSQuQTQrg8PUw6shwmT648zGgwA2cbZ/pu7sslqxgKzpqFha0tV3v05PElI9/7F6wCLWfqku0t6w7J+lNwaO2s+KC/HxLJ2slhJDxMNK7vdCrp4cj4Nv4cuRrDyH9OqgI/ipJJDA0MXdC9OtoLhKQeh/VdJIRoKIQ4I4Q4L4QYnsZ5rYQQUghR0cDxvJXc7dyZ0WAGNhY29N7Ym+sOiRScNROk5Gr3HiRev25cw6Ua6zbAnf1XtwHOgF+4zm62vN+3LLF34vk3+ATJZlpO+n7ZfPSvU4RFhyKYf+CqWfpUFOVFhpb29H7F4ZPWNUIIDTAZaAT4Au2FEL6vOM8B+Bg4kP7hv30KOBRg+nvTkUh6bepFtJuWgjNnkPLgAVe7dcfi/n3jGq7U8/83wO3+xaBL8hfLTZ3OJbl25h47F5wx21/wn9YvQZ0SeRm16iQHL901S5+Kovy/NAODEKJu6j9bvOrQ03Zl4LyU8qKU8gmwCGj6ivO+BX4C1IxjKh8nH6bVn8bDxIf03NiTuEKueE2bRmJUFM6/TyDpnpErd979Gsq2hi3fQNgSgy4pWTUfFRoVInzPDUI3mWc5qcZC8Fu7chR0sSVofgjXY4yrXaEoinFEWn8FCiFGSylHCiFmv+LbUkrZPY1rWwENpZQ9Uz93BqpIKQc8d0454EspZUshxHZgiJTyla+ohBC9gd4A7u7uFRYtWqT/7rK5S48vMenWJFwsXRjkPojc5yJxnjSZZA8P7n0yCGmf/txGIiURv7BRON0/TZjfSGJy++m9RkpJ5F5JbAR41RQ4FjAi2Z8Rrj9I4Zt98XjYWTCiihZrjeDBgwfYG3Hfbwt1/+r+jb3/OnXqhEgpDXtdL6U0yQG0BmY897kzMPG5zxbAdqBw6uftQEVD2q5QoYLMKQ7eOCgrzKsgW69qLWMfx8o9k6fIU2X95IXmzWVSTIxxjT66J+WkylJ+7yXlrXCDLkl8nCSXjj0k/xi4TUZdiTWuXyNsPHlTFhq2Rg5efFSmpKTIbdu2ma3vrEjd/7bMHkKmepP7Bw5LA39/G7zzWQjxgRDiMyHE108PPZdEAl7PfS4APD976gCUAbYLIS4DVYFVOX0C+mWVPCrxS+AvnIs5R9DmIOJK+lBg0kSenDvP1Z69jKsfnctZVwHOKhf81Qpi9W9ms7TW0KhvWbR2VqydEsbDGPMkvqvv687gesVZceQas/ZcNkufipLTGbrz+Q+gLTAQXQ2G1kAhPZcdAooJIbyFENZAO2DV029KKe9LKV2llIWllIWB/cCH8jWvknKyWgVq8VOtnwi7E8a0qGloqlfC8/ffSTh9moievUh+8CD9jTp7QcclEH8PFrSGx/oDjJ2TDR/09+dxfBLrpoaRaKaEewPrFqWBrzvfrztFeLTa36AopmboE0N1KeVHwD0p5WigGi8+DfyHlDIJGABsAE4BS6SUJ4UQ3wghPnyTQedE9QvVZ0zNMZx/fJ4BWwZgWasqnr+MJ/7ECSJ69yHlof7Na/+Rzx/a/Am3wnV5lZL171dwLWBPgx6liboax5Y54WZJuGdhIfilbQA+rnZMPZbALbUzWlFMytDA8HRZyCMhRH4gEdBbxEdKuU5KWVxKWURKOSb1a19LKVe94txA9bSQtsY+jemcpzOHbx1m4JaBWNWpief4n4k/doyIvv1IeWTELuVi9aDxr3BhC6wZbNAeB28/V6q3KMqFI7fNlnDP3saSqZ3K8yQZBi5QNaMVxZQMDQxrhBDOwDh0OZMuo1t+qphZJftKfFfjOw7ePKgLDvVqk/+nH3kUEkJEUH9SEoz4a7pCF6g1FI7OM7jIT0A9L3yfJtw7cDP9fRqhqJsDXUrbcPDyXcZvOmuWPhUlJzI0MPwkpYyRUi5HN7dQEvjOdMNS0tKkSBPG1ByjCw5bB2L9Xl3yj/2BRwcOENl/ACmPjZgYrvPF/xf5CV2o93QhBLXal8CzuDNb553ixgUjN96lU/X8lrSvXJCp2y+w9fQts/SpKDmNoYHhWf5nKeVjKeX957+mmN+z4HDjIB9v/Rib9xuQ77vveLhnD5Eff0zKk3SW6Xxa5Me7FqwaABe3671EY2lBwz5lcXDRsv6PMGLvmGcj2sgmvvjmc+TTJce4pja/KUqG07fz2UMIUQHIJYQoJ4Qon3oEArZmGaHyWk2KNOG7mt9x4MYBBm4diLbp+3h8M5qHO3Zy7ZPByPQGB0traPsXuBaHxZ3h1km9l2jtrGjc35+UZMnaKWE8idefpO9Naa00TOlYnqRkyYAFR3iSpOYbFCUj6XtieA/4Gd0ehPHPHYOBEaYdmmKID4t8yLc1vn0WHHK1+BD3r7/iwdatXPvfEGRiOjOjap10RX6s7WB+a7h/Te8lzu62vNe7DPduPmLDjJOkmGFiuLCrHT+29OPo1Rh+/NfItOSKorxSmoFBSjkXeBfoK6WsK6Wsk3o0lVKuMM8QFX2aFm36LDh8vPVjbNu0wH3ECOI2beLa0M+QSen8K96pgC44JMTq6jgkxOq9xKukC7XbF+fqyWj2LD9v5J2kzwd++ehavTAzd1/i3xPmmQBXlJxA7xyDlDIF6GOGsShvoGnRpnxT4xv239jPoG2DsO3QGrdhw4j791+uD/8cmZzOjWEeZaHNXLh9GpZ8ZNAeh9LveOJf14uwrZGc2Kn/SSMjfP5+SfwLODF02TGuRpunqJCivO0MnXzeJIQYIoTwUoV6sq5mRZsxuvpo9l3fx6Btg7Dr3I68//uU2DVruDHii/QHh6LvQpPf4eI2WD3IoD0O1VsVpVDZPOxcdJaIU6ZPmW1jqWFSh/IIIGhBCAmJame0orwpQwNDd6A/sJN0FOpRzK95sebPgsMn2z7BoftH5B30Mff/+YcbX3+NTEnn+/9ynaD2cAidDzt+1Hu6hYWgQffS5PawZcP0E9y7acSO7HTycrFlfJsATlyLZczaUybvT1HediYr1KNknqfBYe/1vQzaOgiH3t1xDQri/vIV3Bw5Kv3BIXA4BHSE7T/A0b/0nm6dy5IPgvyw0AhdadAHpi8NWt/Xnd61fJi3/wqrjxlZ6U5RFMDwJHq2QogvhRDBqZ+LCSEam3Zoypv4T3AI6kWevn2IWbqUmyNHpi84CKF7peRTR/dK6fwWvZc4uubi/X5+PLj3mPXTjpNshiWlQ98rQYVCuRm+PIyLt41ILKgoCmD4q6TZwBOgeurnSNTO5yzvaXDYc30Pn2z/BMcBfXEN6kfM0mXc+Oqr9AUHjZUu4V7ekrqEezeP673Ew8eJOp1Lcv1cDDsWmr40qJXGgonty2FtaUHQ/CNqvkFRjGRoYCgipfwJXfI8pJTx6NJvK1ncs+BwbQ+Dtw/GsX8fXPv35/7yFdz44sv0TUhrHaHDErBxSN3jEKn3khJVPKj4fmFO7blB6GbTlwbN75yLX9sGcPpmHKNW6d+gpyjKfxkaGJ4IIXIBEkAIUQQwT6UW5Y21KNaCUdVGsfvabgZtG4RDv564DhjA/b//Tn9wcPKETsvgyUNdcEjQnyOpcmNvipR3Y++K81w6dvsN7sQwgSXcGFCnKIsORbA8RH/wUhTlRYYGhpHAv4CXEGI+sAX4zGSjUjJcy+ItdXMO1/YyYOsA7Pp0w/XjgdxfuZIbI0akLzi4l9a9VrpzVpc6Iynt1BvCQvBu11K4FXRg46xw7kQaUXUunT6pV4wq3i58ufIE526Zvj9FeZsYuippE9AC6AosRFebebvphqWYQotiLRhTcwyHbh4iaEsQtr26kPeTQdz/Z1X6N8EVqaNLundpB6z+WO8eBytrDe8H+aG1tWTt5DAe3jftA6dl6nyDnY2GfvOP8OiJ6XM4KcrbwtBVSc2BJCnlWinlGiBJCNHMtENTTKFJkSaMfWcsoVGh9NnUB5vuHck7eDCxq1dz/bNh6UufEdBBl6772ELY9r3e0+2cbHg/yI+ER0msm3qcJBOXBnVz1DKhXTku3H7Al3+fMPnkt6K8LQx+lZSaahsAKWUMutdLSjbUyLsR42qP4+Sdk/Te2Burrm11O6TXruX6Z+nMrVRrqG4T3M6f4Mifek/P6+VA/W6+RF2JZcvcUyYvDVq9qCufvFucFUevsfiQ6Se/FeVtYGhgeNV5lhk5EMW86heqz691fuXMvTP02tgLTedWuA0dQuy69VwbMtTwrKxCQOPfoMi7sPoTOLdZ7yU+AXmp1rwI50OiOLjW9KVBB9QtyjvFXBm56iTh1/UnBFSUnM7QwHBYCPGLEKKIEMJHCPErurQYSjYW6BXIhLoTuBBzgR4be0CHZrh99hlx//6bvuCgsdIl3HP3haVd4MYxvZeUq1+QUtXzcXjtZc4eNG1mVI2F4Ne2ATjbWhE0P4S4BNPvxFaU7MzQwDAQ3Qa3xcBSIAFd7iQlm6vpWZPJ9SYTERtB9w3dSWnXGLfhw4jbsIFrn/7P8OBg4wAdloLWGea3gZi0X9sIIajdoQT5izmz9c/T3Lxo2tKgrvY2TGxfnoh78QxfflzNNyhKGgxdlfRQSjlcSllRSllBSvm5lNL02dEUs6iarypT6k3hxsMbdNvQjcTWDXEf8bmunsOnnxpeCc4xn66OQ2I8zG8F8TFpnq6xtKBRn7LY5bZh3dQwYqNNW6azsrcLQxqUYO3xG8zbf8WkfSlKdmboqqTiQohgIcRGIcTWp4epB6eYTyWPSkyrP4078Xfo9m83ElrUw/2LL4jbtJnIwekIDu6+0HYeRF+AxZ0gKe1lqVp7Kxr39yM5SbJ2sulLg/ap5UPdkm58uyacsMi0A5ei5FSGvkpaChwFvgSGPncob5FybuWYXn8695/cp+u/XXnYrDbuX33Jgy1biBz0CSmGBgef2tB0MlzeBf8M0LvHIbeHHQ1TS4NunHWSFBOuVLKwEIxv7Y+bg5ag+Ue4/0jNNyjKywwNDElSyqlSyoNSypCnh0lHpmSKsnnLMqPBDB4lPaLrv12JbVxDV0N62zaufTzI8ODg3xbqfgnHl8DWb/We7lXKhVrtinPleDR7TVwaNLedNZM6lONWbAJDlh1T8w2K8hJDA8NqIUSQECKfquD29vPN48vMBjNJSkmi24Zu3Hu/Ch6jRvJg+3Yi+w8gJd7AuYB3hkD5LrBrPByerff0MrU88atbgGNbIkxeGrRcwdx83qgUm8JvMXO36ZfMKkp2Ymhg6ILu1dFeVAW3HKGESwlmvTcLgO4buhPVoBz5vvuWh7t3E9GrN8kPDKh3IAR88AsUrQ9r/wdnN+q9pEarYhQsnVoa9LRpS4N2q1GYhqU9GLv+NCFXTF+GVFGyC1XBTXmtIs5FmP3ebCwtLOmxsQfX6/iS/+dxPAoN5WrXbiTdu6e/EY0ltJ4DHmVgaVe4fjTN0y0sBO/1TC0NGmza0qBCCH5q7Ud+51wMWHCUuw8NfE2mKG+5NAODEKLFS0dzIcQ7QggHcw1QyVyFnQoz57052Fra0nNjT65WLkiBiRN4fPYsVz/6iMSoKP2N2Njr6jjY5tGl6o6+kObp5iwN6qi1YkrH8kQ/eMLgxaEmnfhWlOxC3xNDk5eOD4EhQJgQoq6Jx6ZkEV6OXsxpOAdHa0d6bOzByZK58AoO5sm161zp1JknkQbMBzh4QKflkJIMf7WAuFtpnu7omotGff2Iu5fAv8GmLQ1axtOJr5v4suPsbabuSDtoKUpOkGZgkFJ2e8XRFAgEfjDLCJUsIb99fv5s9Cee9p4EbQ5ib75YCs2aSXJMDFc6deLxRQMmcPMW122AexAF81tCQtp5i/IVcaJu51JcOxvDjgWmLQ3asUpBPvTPz/iNZ9h/Mdpk/ShKdmDo5PMLpJRXAKsMHouSxbnZujGn4Rx88/gyZMcQ1tqep9C8P5GJiVzp1ImE06f1N1KgIrSZB1GnYFEHSExI8/RnpUH33iB0k+myowoh+L5FWQq72jFw4VFux6kChUrOZVRgEEKUQJX2zJGcbJwIrh9MtfzVGL1vNPOf7KbgvD8R1tZc+agLj46mPbkMQLF60HSKbgPc3711r5fS8Kw06N/niY003VODvY0lUzqWJy4hkUGLjpKs5huUHErf5PNqIcSql47dwDrgU32NCyEaCiHOCCHOCyGGv+L7nwohwoUQYUKILUKIQsbfimIutla2TKwzkUbejfjtyG9Mvvs3hf6ahya3M1d79OThvn36G/FvC1VEieEAACAASURBVA3GQPg/sP6zNHdHP18aNHKf5MZ506WyKOnhyDdNy7D3QjS/bzlnsn4UJSvT98TwMzD+ueNnoA9QSkqZ5v/9QggNMBloBPgC7YUQvi+ddhRdmVA/YBnwU7rvQMkUVhorxr4zlnYl2jHn5By+vTKNAn/OxdrTk4g+fYnbuk1/I9UHQPWP4dAM2JH2f3oraw2NB/hjZQtrp4QRfc2AfRRGalPRi1YVCjBx6zl2nr1tsn4UJavSFxh2Sil3PHfslFKelFI+W/AthBCvubYycF5KeTH1/EVA0+dPkFJuk1I+Sv24Hyhg5H0omcBCWDCiygj6+fdj5fmVfHbyezzmzMCmRAkiBw7k/pq1+hup/w34d4Dt38PhWWmemsvBmkK1BZZWFqyeEErsHdNlY/22aRmKuznwyeJQbt5Pex5EUd42+gLDNiHEQCFEwee/KISwFkLUFULMRbcr+lU8gednCyNTv/Y6PYD1+gasZC1CCIICghheeTjbIrYx4PBw8kybgG25clwfOpR7i5foawA+nADF3tPtjg5flebp1vaCJh8HkJSYwqoJoTyKNc2mtFzWGiZ3LE9CYjIDFx4hKdl0y2UVJasRaS0BFEJoge5AR8AHuAdoAQ2wEZgspQx9zbWtgf9r78zjqirzP/7+3su+iyAoqCii5opCZlpmpWlWLpVpaWWZbbZNNTM1TU3T9pv2aZ3Mdht1LEvNTKdFrWxRXHDBJUVUVEARUVCQ5fv74xwSmAtCcdl83q/XeXHuc5/znO/3nsP5nGf7PsNU9Sb787VAP1W900XeicAdwHmq6rJTW0RuBm4GiIiISJg9e3ZNfWxW5OXlERAQ0NBmuGRV3io+zP6QKK8obg+ZTPRbs/DetImjV1zBsaFDqj3WUVJI7+SHCTyaSnLvR8kN6eEyX5n/xw4oacsU7yCIuUBwelZVcf19/LivmGnrCxnRwZOruni55Ry1oTFf//rA+P/b/T///PNXq2pijTKrao02rOGprYGQGuY/G1hS7vODwIMu8g0BNgOtampLQkKCnq4sXbq0oU2oluV7lmvijES99JNLNf1Qmu65+x5N6dJVs15+RUtLS6s/OD9b9ZUzVZ+KVt2/3mWW8v7vTD6gr932jc57cY0WnyipQy8q8uAn67X9nxfqVykZbjtHTWns19/dGP+X/uZjgSSt4TP2VKOSfETkHhF5FbgBOKCqNR0SsgqIE5EOIuIFjAcqtBOISB9gGjBSVWsQW8HQ2BkUPYg3L3qT7IJsrvvqRgoevo3gyy/n4GuvkfWPp6ufpOYXCtd+Yi0T+uEVkJNW7blieoVxwXVdSd+Sw5fvprgtnMUjl3ajW+sg7p2TTHrOsVMfYDA0cU7Vx/A+kAhsAEZgjUyqEapajNU8tASrRjBHVTeJyGMiMtLO9iwQAHwkIutEpPoGZkOToE+rPrw77F1KtZRJX95I9t1X0eLaazn0/vvs/8tD1a8jHRwNEz+xVn6bMQbyqh8V1LV/awZc0Ykda7L47j/b3DI72sfTyesT+lJaqlz/zkp2ZxtxMDRvTiUM3VR1oqpOA64Ezq1N4aq6SFU7q2qsqj5ppz2iqgvs/SGqGqGq8fY2svoSDU2FLqFd+ODiDwj0DGTyV1PYOWkwYVOnkvvpp+y55dbqw3a36mqFzjiy31o7uvBotefqM7QdfS5qx8ble1n1eVrdOmITE+bPW9cncjDvBGNeX2HCdBuaNacShl9f7ewagMFQY9oGtuWDiz+gbWBbbv9mKmsv60zrJ58gf+VKdk2YSFFGRjUH94Or3oeMDfba0dWPPjp7TCxdz45k1cKdbFiWXseeWJzVsSWf3j6AQB8Prp7+MwuS97nlPAZDQ3MqYegtIkfs7SjQq2xfRKqPgGYwAOF+4bw7/F16hfXi/uX3s6R7MW2nvUFRejpp48ZXH1+p8zAY9SqkLoN5t0Jp1UNGRYTzJ3YlpmdLvv3PNn5Jqj5662+lY3gAn9w+kPjoEO6atZaXv/7FLA1qaHacKrqqU1WD7C1QVT3K7QfVl5GGpk2QVxBvDH2D86LP44mfn+AVj2+J/vB9AHZNmEje9yuqPjj+Ghjyd9g4FxY/UG3oDIfTwUVTetA6Npiv3k1hz2b3NPeE+nsx46Z+XN4nihe+3MZ9c5IpLK4+3pPB0JT4TUH0DIba4uvhyz/P/yfXd7uemVtmcm/6y4TNmI5ndDR7brmFw3PnVn3wwLvh7Dtg5TRi0mZXKw6eXk5G3NaLFpF+fPHGBrJ2uadi6+3h5PmrenPf0M58snYv1761khyzApyhmWCEwVBvOB1O7j/zfh4b8BgrM1Zy3ep7cfzrKfz792f/Q3/lwMsvu26WEYGhj0P8BGJ2zYb//rVacfDx9+SyO+PxCfDks1eSOZzpnlFEIsKdF8bx0vh41qUfZszrK0g94L4YTgZDfWGEwVDvjIkbw1sXvUVuYS4Tlk9h/6M3EHzF5Rx8/V/sf+AB9ISLN2+HA0a+SnrUJfDjqzD/DiipejyEf4g3I++KRwQWvLSOvBz3RYkfFR/FrClncbSgmDGv/8CPO8xCP4amjREGQ4OQEJHAzEtm0sqvFbcsncp3E3sSfvdd5M5fwO4pN1NyxEUTkMPB9k5TYPCDsO5D+Oj6ahf6CYnw49I7elOQX8Rnr6yjIN99a0cntA/l09sHEh7ozXXv/MxHSe5bVMhgcDdGGAwNRnRgNDMunsHAqIE8sfJJpvU5RMQ/nuLYmjXsmjCBon0uhoOKwOAHYPjTsGUhzBxb7TyHVu2DGHFbTw5nHWPR6+spOuG+TuJ2Lf2Ye9sA+nUI5Y8fr+fZJVvcNhvbYHAnRhgMDUqAVwAvn/8yk7pPYvbW2fzZbxEtX3uRooxMdo4bx/FNm1wf2P9WGDMN0lbA+yPhWNUjkKK7hjL0hu7sT81l4SvJ5Oe6r1kp2NeT927ox/gz2/La0h3cOWstBUVmxJKhaWGEwdDgOB1O7ku8j8cGPEZSZhKTs/+J55vPIh6e7Lr2OvKWL3d9YO/xMP7fkLkJ3r0YjlQ94axTQiuG3tCNrLQjzHlyFXu35bjJG/B0Ovi/y3vylxFdWbRxP+Pf/MmsIW1oUhhhMDQaxsSN4e2L3ia3MJeJWx4k+6X78Yppz57bp5Iz+z+uD+pysRV4L3cvvD0MsndUWX7nfpFc+UAiXr4ezH9xLasXp6FuauoREW4eFMu/JiSwJeMIo19bwbbM6kN7GAyNBSMMhkZF34i+zLxkJhF+Edy67i8kPTwa/4EDyHj0UbKef8H17OeYc2DSZ1CUD+8Mt8JoVEHLqADGPphIbEIrfpqXyqJ/rXdrp/TwHpHMueVsTpSUcsXrP/D1ZvfMyDYY6hIjDIZGR1mn9DlR5/D4+meZcX00QWOvJHv6dIKnT3c9YqlNH7hhMTi94N1LYPdPVZbv5ePBRZO7M2h8Z3anHGLOk6vITHNfhJde0SHMnzqQ6FA/Jr+fxF2z1pJ11CwXami8GGEwNEoCvAJ46fyXuKH7Dcze/hF/O2cfQffeiXfyenaOHsPxdS4WDgzvDDcuhoBw+GA0/PJlleWLCD0HR3P5/QkoyifPrWbDsnS3xT1qE+LLvKkDuGdIHIs3ZjDk+eXM/Hm3GbVkaJQYYTA0WpwOJ/cm3svjAx9nddYabglfxPZ7bgAR0iZey8Hp09HKTUshba2aQ1gczBoPGz6u9hwRHYIY91A/2p4Ryrezt/Hl25s4UeCeQMLeHk7uGdKZL+45l25tgvjLpxsYO+1HtmaYvgdD48IIg6HRM7rTaN6+6G2OnjjKoz4zSXr6agIuvIADz7/Anik3U3zwYMUDAsJh0kJoexbMvQlWvV1t+T7+nlxyWy/6j+7I9tVZfPR/SWTvdV9oi9jwAGZN6c9zY3uTeiCPS17+jmcWbzHDWg2NBiMMhiZB34i+zLl0DnHecTy56Z88MjwX7wfv4VhSEqmjx5C3olKEVp9gmDjXCt39+b3w7XPVxlcSh5AwPIZR9/Sh8HgxH/8jiS0/7XebPyLClQnRfH3fYEb3ieL1ZTu46MVvWb6t+hXrDIb6wAiDockQ4R/Bra1u5bEBj7E5ZwvjPd5m67OTcQYHs+emKWQ9/0LFZUM9fWHch9BrHHzz+CmD7wFEdWnBuIfOJKJDEF+/t5mlMzZT7MbZ0qH+Xjw3tjczp5yFh0O4/p2V3DVrrZn3YGhQjDAYmhQiwpi4MXw68lN6h/fmr/vf5PnbIvAaPYLs6dPZde11FO3de/IApyeMfgP63WIF35s9odq5DgD+wd6MvDuehOHtSVmxn7nPruZwlnvXeR4QG8aiu8/l7gutzukLn19mOqcNDYYRBkOTpHVAa94c+iYP93+YpNwNTOy5gr1/Gk/h9u2kjrmcI0v+ezKzwwEXP22F7k5dCq/1g0V/gvyDVZbvcDroPzqWS6b24uihAj56ahU71ma51ScfTyd/GNqZRXefyxmtTee0oeEwwmBosogIV3W5irkj59I1tCt/cH7Mu/f3QNq2Ye/dd7P/73+ntKCgLDMMvAvuWgt9roVVb8FL8Vbfw4mqawMxPcO46i9nEhLpz+JpG/nmg80cOXjcrX51ahXA7Jv78+yVvUzntKFBMMJgaPK0DWzL28Pe5oF+D/B18UYmj8kg5/JBHJ41m7SrxlG4o1zTUWAkXPZPuP1H6DDI6nt4pS+smQGlrh+8QS19ufz+vsQPbcfWlRl8+MhPfPVeCjkZ+W7zSUQYm9iWr+8bzKj4k53Ta7OKzRrTBrdjhMHQLHCIgwlnTOCjyz4iJrQTt3T5gc+n9uFEViY7rxzL4blzKz5Qw7vA1TPhhi8gKAoW3AH/GgjblrjsoHZ6OBh4RSeue2IAvc6PZseaLGb+/WcWv7mRA3vc19QT6u/F81ed7Jx+aU0hI17+ngXJ+ygx/Q8GN2GEwdCsiAmO4b3h73Ffwn3MCtnK/Tc6ONYlmv0P/ZV99/+RkrxK8xPaD4CbvoKx70NJIcy8Ct6/DPaucVm+f4g354yN47onB5AwrD17UrKZ8+QqFr6WTEZqrtv8GhAbxpI/DGJKTy+KSkq5a9ZaLnh+GbNW7qaw2DQxGeoWIwyGZofT4WRSj0nMuWwOgW3aM2lYKkmjOnPkiy/YfuEQMp95lhN7yq2wJgLdR8PUlTDiOcjaDNPPh49vhEM7XZ7DN9CL/qNjue6pAZw1sgOZqUeY+8xq5r24lvStOW5p7vF0OhgY5cl/7xnEGxMTCPH15MFPNjDomaVM/zaV/EL3zNg2nH4YYTA0W2JDYpkxYgZ3JtzNCz1289RNwRzu0ZZD77/PjouGsefW28j7fsXJsBpOT+g3xeqgHvRH2LIIXj0TvngA8l2v4+zt50niiA5c++TZDLiiEzn785n/4lo+eXY1aRsOukUgHA5heI9I5k0dyIeTzyI2PIAnF21m4NPf8OKX28jJd7FmtsFQCzwa2gCDwZ14ODyY0msKg6IH8fCKh7mp5WbaJPoweUc03VesIW/ZMrxiYmgxYQLBY0bjDAgAnyC44K+QOBmWPQUrp8G6f8M5f4CzbgUvv/85j5ePB32GtqPn4Ci2/LCf1Ut28flr6wlrG0DixTF0jA9HHFKnvokI58SFcU5cGGt35/D6sh289PUvTP8ulWv6teOmczsSGexTp+c0nB5IUxzhkJiYqElJSQ1tRoOwbNkyBg8e3NBmNBi/x39VJflAMvO2z2NJ2hIKjh/l4p0hjFznQfD2TBx+fgSPHk2LCdfgHRt78sCsLfDVo7DtC/AKsMJsnDES4oaCl7/Lc5WUlLLt50xWL04jN+s4LSL9SLg4hrjEVjicv72ifir/t2Yc5Y3lO1iQvA+nCFckRHHLoFhiwlzb2dQw9/9v919EVqtqYo3yGmFoWph/jLrxv6C4gG92f8OCHQv4Yd8PdNxXyjWbQui+7jCO4hL8B5xNiwkTCBg8GHE6rYN2/QjJM2HL53AsGzx8odOFlkh0GW7FZ6pEaamyY00Wq79II3tvPr6BnnToHU7HPuFEd2mB06N2IlFT//ccOsa0b3cwJymd4pJSLunVhtvOi6Vbm6Bana+xYe7/+hEG05RkOC3x8fBhRMcRjOg4goz8DBamLuTDMxaQPeAww9Z7MSJ5LflTf8SjTRtCr7ma4CuuwKP92dD+bLjkRdj9I2xeAJs/gy0LweEJHQdDt5HQ5RLwbwlY/QFxiRF06tuKtI3ZbFuZwS+rMkn5fh9ePk7a9wyjY3w47bqH4uVTd/+ObUP9eGJ0T+66MI53vk/jw5928VnyPs7u2JIRPSO5qHskEUGmmcngGlNjaGKYNyb3+a+qbDi4gfnb57MkdRFdNx5h5FoP4tJOgLcXwZdeSvBll+HbsycOf7tpprQU9iZBynxLKA7vBnFCzECrJnHGZdakunIUF5WQviWH1LUH2Ln+IAV5RTg9HbQ9I5TYPuHE9ArDx9+zTv3PPVbEhz/vYu6adFIPWBPz+rQLYXj3SIZ1j2wyTU3m/jdNSVVihGFwQ5vRYNSX/4UlhSzds5T52+ezZ933XJRUwnkpgteJUtQheMZ1IiC+L77x8fj27o1XhxgEYH+yJRApCyD7F0CsdSG62SIR0q7CeUpLStm/PZfUdQdIXXeAvJxCxCFEdQ6hY3w4HXqHE9DCu0793551lMUbM1i8KYONe60lTbtGBjKseyTDe0TSNTIQkbrtKK8rzP1vhKFKjDAMbmgzGoyG8D/rWBafp37Oko2f4pmyg7i9Stw+6LIffAus/5/SQD98e/UmsG8Cvr3j8e3dC+fxvSdFInODVVhYZ4jsBa172X97g18oYNVYDuw+SupaSyRyMqwYThEdgugYH07H+HDWbV5Zp/7vOXSM/6ZksmRjBqt2HUIV2rf0Y5hdk+jTNgRHHY+m+j2Y+98IQ5UYYRjc0GY0GA3tf05BDpuzN5NyKIWUA5vI3ppM8C+ZdN6rxO1Tog+CQ0EFStq1JqBPAiF9z8S3Q0u8jycje1fB/vVwJP1koUHR5YTC/hsczaGMY6SuO8DOdQfI2mWF3fD0gzYdWxLaxt/aWvvTorU/nl7O3+3bgaOFfLU5k8UbM/hhx0GKSpRWgd6/isRZHUPx/B0jquqChr7+DU2z6HwWkeHAS4ATeEtV/1Hpe2/gAyAByAbGqWqaO20yGH4PLXxaMCBqAAOiBlgJF0BuYS6bD20mJTuF5enrObY+meDtWcTtzSBuyUIK5i0EoNjXi5IOUXi06Y9/ZCSBwV74eB3FU/fhmbkNx9YvAPtFzTeU0MiehLbuReIlvTnq243U3QFs+HkHeTmF7NlyiNJiO69AUJgvoa39aVkmGG38aRHhj9Oz5g/y8EBvru7Xjqv7teNIQRFLt2SxeGMGH69OZ8ZPuwj29aR/x1BiwwOIDQ+gY7g/HcMDCPZ13R9iaLq4TRhExAm8BgwF0oFVIrJAVVPKZZsM5KhqJxEZDzwNjHOXTQaDOwj2DqZ/6/70b90fegDD4ciJI2w9tJWUg5vYs3kVRes3Err9IG0OpRGetBM9AgWlFcs5HtyBopb+EOKFV0ApAbv3EaKrCfIpwN+vmN6+fsR6tSIgugOlZ0SQSzsOnYji0PFQsnOVQ/tPsHvjQcomcotDCA73/bVmEdrGn6AwX3z8PfD288TL16PKZqIgH09GxUcxKj6K4ydK+O6XAyzelMG6PYf5enMWxeUC+IUFeNExzBKK8oLRtoUvHg1cwzD8NtxZY+gHbFfVVAARmQ2MAsoLwyjgUXv/Y+BVERFtiu1bBkM5gryCODPyTM6MPBN6TIKxkF+UT/rRdDKPZbL1aAaH96ZSkL6b4n37cWYcxOfAUYJyDtEqVfE7AsWlcJAgDmLNPcj3d3Dcrxj1+oVSj22oRzE4SxFPxddDaeuhtPMQij0iKPKOodAzhuO5bcnMiWDn2hCUyiKgeHuDt4/g7efA29eJj58lGt4BXnj7e+ET6IO3vy/dA7zpOyAWT28npcC+IwXszjnOrpx80rKPsyM7jy83ZTL72MkYVJ5OoV2oHx1tsYgNCyAy2AcvD4e1OSv9LZfu7eFotB3gpwPuFIYooFykMtKBs6rKo6rFIpILtASqXlrLYGii+Hv60yW0C11Cu1gJZ/xvnoLiArKOZZF5dD/Ze7dzdHcqhel7KN2XgUfmIRw5+fgUKx6FxXjne+B9QvE9AT4nwOPXGshhYJ29WZQ4PDjmF0mhdwhFHn4Ue/hR5OlHsYc/RfZ+rqcf2fZ3xR7+qKNm/RZt7W0wTlBvREuBEkRLkcwjSEoOaCmHtYRclF+by6ji/c/le+HJtO3v/btGdjVHRPPrpY/FncLgSu4rX/Ga5LEyitwM3AwQERHBsmXLfpdxTZW8vLzT1nc4vfz3IQqfsCgIA+KttLy8PAICAn7NU6Ql5OsJirSIEyfyKSnIp7ggj9Lj+ZQWHEMLj0OBtTmOH0OKCpDSY0hJKZSW4CgtgdJSpLQU75ISfFSR4lIoLIVSDxRfFB9780XxAhyoOCv8BSf662cniAPFzoMDxP7+17idVdUGTqari7TTHimol/vfncKQjvUiUUY0sK+KPOki4gEEA4dcFaaqbwJvgjUq6XQdmWBGZRj/jf+DG9qMBqO+/Hdnz9AqIE5EOoiIFzAeWFApzwLgenv/SuAb079gMBgMDYvbagx2n8EdwBKs4arvqOomEXkMSFLVBcDbwAwR2Y5VUxjvLnsMBoPBUDPcOo9BVRcBiyqlPVJuvwAY604bDAaDwVA7zCBjg8FgMFTACIPBYDAYKmCEwWAwGAwVMMJgMBgMhgoYYTAYDAZDBZpk2G0ROQDsamg7GogwTu+QIcZ/47/x/7fRXlXDa5KxSQrD6YyIJNU0pnpzxPhv/Df+u99/05RkMBgMhgoYYTAYDAZDBYwwND3ebGgDGhjj/+mN8b8eMH0MBoPBYKiAqTEYDAaDoQJGGBopIjJcRLaKyHYRecDF9/eKSIqIrBeRr0WkfUPY6S5O5X+5fFeKiIpIsxqpUhP/ReQq+x7YJCIz69tGd1KD+7+diCwVkbX2/8CIhrDTHYjIOyKSJSIbq/heRORl+7dZLyJ969wIVTVbI9uwwpTvADoCXkAy0K1SnvMBP3v/NuA/DW13ffpv5wsEvgV+AhIb2u56vv5xwFqghf25VUPbXc/+vwncZu93A9Ia2u469H8Q0BfYWMX3I4AvsJa26w/8XNc2mBpD46QfsF1VU1X1BDAbGFU+g6ouVdVj9sefsFbIay6c0n+bx4FngIL6NK4eqIn/U4DXVDUHQFWz6tlGd1IT/xUIsveD+d/VIZssqvotVaxkaTMK+EAtfgJCRKR1XdpghKFxEgXsKfc53U6rislYbxDNhVP6LyJ9gLaqurA+DasnanL9OwOdRWSFiPwkIsPrzTr3UxP/HwUmikg61povd9aPaY2C2j4fao1bF+ox/GZcrX7ucviYiEwEEoHz3GpR/VKt/yLiAF4EJtWXQfVMTa6/B1Zz0mCs2uJ3ItJDVQ+72bb6oCb+Xw28p6rPi8jZWCtB9lDVUveb1+DU+PnwWzE1hsZJOtC23OdoXFSVRWQI8BAwUlUL68m2+uBU/gcCPYBlIpKG1c66oBl1QNfk+qcD81W1SFV3AluxhKI5UBP/JwNzAFT1R8AHK47Q6UCNng+/ByMMjZNVQJyIdBARL6y1sBeUz2A3pUzDEoXm1L4Mp/BfVXNVNUxVY1Q1BquPZaSqJjWMuXXOKa8/MA9rAAIiEobVtJRar1a6j5r4vxu4EEBEzsAShgP1amXDsQC4zh6d1B/IVdX9dXkC05TUCFHVYhG5A1iCNULjHVXdJCKPAUmqugB4FggAPhIRgN2qOrLBjK5Dauh/s6WG/i8BLhKRFKAE+KOqZjec1XVHDf2/D5guIn/AakaZpPaQnaaOiMzCaiIMs/tQ/gZ4AqjqG1h9KiOA7cAx4IY6t6GZ/JYGg8FgqCNMU5LBYDAYKmCEwWAwGAwVMMJgMBgMhgoYYTAYDAZDBYwwGAwGg6ECRhiaOSISUzlKo4g8KiL3u/m8o0WkWw3y3Soi150iT/xviZ5p2/CIvT9IRNaISLGIXPkbyhpsR3GdXC6tj532u39L+5rsFZF1IrJRRGo19Liqayoi4SKy2EV6T/tc60TkkIjstPe/sn2t81AjIjJJRF6t5TFp9jyNyuluv4dPZ4wwGOocEfEARmNFvawWVX1DVT84RbZ4rHHbteVPwOv2/m6sEBq/Jzz1BmBcuc/jsSJ/1hUvqmo8MBZ4xw798Sv271orVPUAsF9EBlZK36Cq8fb5FmDNg4hX1SE1LVtEnLW1x9A0MMJwmiMiy0TkaRFZKSLbRORcO90pIs+JyAY75vuddnqCiCwXkdUisqQsqqNdzlMishz4MzASeNZ+C40VkSkiskpEkkVkroj42cf9+ubnyhZ75utjwDi7rHEi8ouIhNvHOMSKSx9Wya/OQKGqHgRQ1TRVXQ/8nlg6uwEfEYkQa1bhcMoFL6zGx/lltSIRuUVE/l3dSVR1M1CMNcHpPRF5QUSWAk+LSKiIzLOvyU8i0qvcob1F5Bv795lSLn0eMKGWvgaIyMciskVE/m37W/YG/4iIfA+Mta/tYvt++E5Eutr5xto1n2QR+bZcuW3s/L+IyDPlfrur7Xtto4g87cogEXlIrDUavgK61NIfQy0wM58NAB6q2k+s5pq/AUOAm4EOQB97JmqoiHgCrwCjVPWAiIwDngRutMsJUdXzAEQkDlioqh/bnw+r6nR7/wmsWDevnMoWVR0iVnNQoqreYR/fFetB90/b1uQyASjHQGBNXfw4lfgY641+rV1++RhVn1Th483AChHZiTVjt391JxCRs7AErCzEQ2dgiKqWiMgrwFpVHS0iFwAfYNWoAHrZZfsDa0Xkc1XdByQBT9TSzz5Ad6wYPCuwfs/v7e8KVPUc29avgVtV9RfbgW0RagAAA85JREFU7teBC4BHgGGquldEQsqVG2+XXQhstf0pAZ4GEoAc4L8iMlpV55X7TRKwamh9sJ5ba4DVtfTJUEOMMDR/qpraXj79E/vvaiDG3h8CvKGqxQCqekhEemAFr/vSfoF0AuVjtPynGjt62A/LEKxQHkuqyOfKlsq8A8zHEoYbgXdd5GmNe2LnzMHysyswCxhQ7juXPqpqpi1uS4ExqlpVrP0/iBUt9ygwTlXV/p0/UtUSO885wBV2ud+ISEsRCba/m6+qx4Hjdg2jH1ZtIQtoU0s/V6pqOoCIrMO6FmXC8B87PcD2vywsC4C3/XcF8J6IzOHkNQX4WlVz7eNTgPZAS2CZ3eyFXaMaZNtexrnAp2VrkIhIsw6L0tAYYWj+ZAMtKqWFAjvLfS576y3h5D0h/K+oCLBJVc+u4lz51djxHjBaVZNFZBJWLBhXuLKlAqq6R0Qy7Tfms3DdTHIcawGXGiMiU7EWwAEYYb9tVz53hogUAUOBu6koDO9RtY89sa5FdQ/oF1X1ORfp5X/X6kIuV75eZZ99sH6P2lC+JlT5WpTZ4wAO2/0UFU+seqtdg7gEWCciZXlclevKJ1eY+D31hOljaOaoah5W52NZJMpQrLbx76s9EP4L3Cp2h6d93FYgXKz494iIp4h0r+L4o1jhscsItO3wpPbt3ZXLAngL+BCYU+5tujybgU61OYmqvlbWIetKFMrxCPBnF+d16aOI9AMuxmoGuV9EOtTGrkp8W1a2iAwGDqrqEfu7USLiIyItsURplZ3eGXC5fvDvwT7vThEZa9sjItLb3o9V1Z9V9RHgIBXDRFfmZ+A8EQkTq0P7amB5pTzfAmNExFdEAoHL6tofw0mMMJweXAf81W4S+Ab4u6ruOMUxb2F1tq4XkWTgGnuZxSuxOkGTgXVUfGMuz2zgj2It1h4LPIz1APgS2FJL+5cC3cTufLbTFmA117hqRgLrQdKnXKfpmWJFqhwLTBORTbW04VdU9Yfy7d/l+B8fRcQbmA7caIvNfVgjjmr6llyZR4FEEVkP/AO4vtx3K4HPscKQP15O3M63093BBGCyfT9s4uQSnM+WdSZjXYsqR2/ZIaMfxLrOycAaVZ1fKc8arCasdcBc4Lu6dsRwEhNd1dAkEWtRnhdV9dxq8rwEfKaqX9WfZY0Pe1TQqLL1oQ2GU2FqDIYmh4g8gPXW+OApsj4F+LnfosaLWMN6XzCiYKgNpsZgMBgMhgqYGoPBYDAYKmCEwWAwGAwVMMJgMBgMhgoYYTAYDAZDBYwwGAwGg6ECRhgMBoPBUIH/B/FRLPDfb6eUAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(1 - unc_thresholds, drop_mean_unc, label = 'Dropout')\n",
    "plt.plot(1-unc_thresholds, swa_mean_unc, label = 'SWA')\n",
    "plt.plot(1-unc_thresholds, swag_mean_unc, label = 'SWAG')\n",
    "plt.plot(1-unc_thresholds, swag_diag_mean_unc, label = 'SWAG-Diag')\n",
    "plt.plot(1-unc_thresholds, sgd_mean_unc, label='SGD')\n",
    "plt.ylabel('P(Uncertain | Inaccurate)')\n",
    "plt.xlabel('Uncertainty (1 - Max Prob) Threshold')\n",
    "plt.grid()\n",
    "plt.legend()\n",
    "plt.savefig('/home/wesley/Documents/Papers/udl_paper_source/icml/plots/pics/segmentation_unc_inacc.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(1 - unc_thresholds, drop_pa, label = 'Dropout')\n",
    "plt.plot(1-unc_thresholds, swa_pa, label = 'SWA')\n",
    "plt.plot(1-unc_thresholds, swag_pa, label='SWAG')\n",
    "plt.plot(1-unc_thresholds, swag_diag_pa, label = 'SWAG-Diag')\n",
    "plt.plot(1-unc_thresholds, sgd_pa, label='SGD')\n",
    "plt.ylabel('PAvPU')\n",
    "plt.xlabel('Uncertainty (1 - Max Prob) Threshold')\n",
    "plt.grid()\n",
    "plt.legend()\n",
    "plt.savefig('/home/wesley/Documents/Papers/udl_paper_source/icml/plots/pics/segmentation_pavpu.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.savez('/home/wesley/Documents/Papers/udl_paper_source/icml/plots/data/segmentation/patch_analysis.npz',\n",
    "        unc_thresholds=unc_thresholds,\n",
    "        drop={'acc':drop_mean_acc, 'unc':drop_mean_unc, 'pa':drop_pa},\n",
    "        swa={'acc':swa_mean_acc, 'unc':swa_mean_unc, 'pa':swa_pa},\n",
    "        swag={'acc':swag_mean_acc, 'unc':swag_mean_unc, 'pa':swag_pa},\n",
    "        swag_diag_pa={'acc':swag_diag_mean_acc, 'unc':swag_diag_mean_unc, 'pa':swag_diag_pa},\n",
    "        sgd={'acc':sgd_mean_acc, 'unc':sgd_mean_unc, 'pa':sgd_pa})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fbfba4aef60>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams[\"figure.figsize\"] = (12,8)\n",
    "plt.subplot(221)\n",
    "plt.plot(1-unc_thresholds, drop_mean_acc, label = 'Dropout')\n",
    "plt.plot(1-unc_thresholds, swa_mean_acc, label = 'SWA')\n",
    "plt.plot(1-unc_thresholds, swag_mean_acc, label = 'SWAG')\n",
    "plt.plot(1-unc_thresholds, sgd_mean_acc, label = 'SGD')\n",
    "plt.xlabel('Uncertainty (1 - Max Prob)')\n",
    "plt.ylabel('Mean Patch Accuracy')\n",
    "\n",
    "plt.subplot(222)\n",
    "plt.plot(1 - unc_thresholds, drop_mean_unc, label = 'Dropout')\n",
    "plt.plot(1-unc_thresholds, swa_mean_unc, label = 'SWA')\n",
    "plt.plot(1-unc_thresholds, swag_mean_unc, label = 'SWAG')\n",
    "plt.plot(1-unc_thresholds, sgd_mean_unc, label='SGD')\n",
    "plt.ylabel('P(Uncertain | Inaccurate)')\n",
    "plt.xlabel('Uncertainty (1 - Max Prob) Threshold')\n",
    "\n",
    "plt.subplot(223)\n",
    "plt.plot(1 - unc_thresholds, drop_pa, label = 'Dropout')\n",
    "plt.plot(1-unc_thresholds, swa_pa, label = 'SWA')\n",
    "plt.plot(1-unc_thresholds, swag_pa, label='SWAG')\n",
    "plt.plot(1-unc_thresholds, sgd_pa, label='SGD')\n",
    "plt.ylabel('PAvPU')\n",
    "plt.xlabel('Uncertainty (1 - Max Prob) Threshold')\n",
    "plt.legend()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
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